A bacterial index to estimate lake trophic level: National scale validation

Bacterial and Archaeal Communities in Erhai Lake Sediments: Abundance and Metabolic Insight into a Plateau Lake at the Edge of Eutrophication

The littoral zones of lakes are potential hotspots for local algal blooms and biogeochemical cycles; however, the microbial communities within the littoral sediments of eutrophic plateau lakes remain poorly understood. Here, we investigated the taxonomic composition, co-occurrence networks, and potential functional roles of both abundant and rare taxa within bacterial and archaeal communities, as well as physicochemical parameters, in littoral sediments from Erhai Lake, a mesotrophic lake transitioning towards eutrophy located in the Yunnan-Guizhou Plateau. 16S rRNA gene sequencing revealed that bacterial communities were dominated by Proteobacteria, Bacteroidetes, and Chloroflexi, while Euryarchaeota was the main archaeal phylum. Co-occurrence network analysis revealed that keystone taxa mainly belonged to rare species in the bacterial domain, but in the archaeal domain, over half of keystone taxa were abundant species, demonstrating their fundamental roles in network persistence. The rare bacterial taxa contributed substantially to the overall abundance (81.52%), whereas a smaller subset of abundant archaeal taxa accounted for up to 82.70% of the overall abundance. Functional predictions highlighted a divergence in metabolic potentials, with abundant bacterial sub-communities enriched in pathways for nitrogen cycling, sulfur cycling, and chlorate reduction, while rare bacterial sub-communities were linked to carbon cycling processes such as methanotrophy. Abundant archaeal sub-communities exhibited a high potential for methanogenesis, chemoheterotrophy, and dark hydrogen oxidation. Spearman correlation analysis showed that genera such as Candidatus competibacter, Geobacter, Syntrophobacter, Methanocella, and Methanosarcina may serve as potential indicators of eutrophication. Overall, this study provides insight into the distinct roles that rare and abundant taxa play in the littoral sediments of mesotrophic plateau lakes.

Maximising environmental pressure-response relationship signals from diatom-based metabarcoding in rivers

DNA metabarcoding has been performed on a large number of river phytobenthos samples collected from the UK, using rbcL primers optimised for diatoms. Within this dataset the composition of non-diatom sequence reads was studied and the effect of including these in models for evaluating the nutrient gradient was assessed. Whilst many non-diatom taxonomic groups were detected, few contained the full diversity expected in riverine environments. This may be due to the performance of the current primers in characterising the wider phytobenthic community and influenced by the sampling method employed, as both were developed specifically for diatoms. Nevertheless, the study identified considerable diversity in some groups, e.g. Eustigmatophyceae and a wider distribution than previously thought for freshwater Phaeophyceae. These results offer a strong case for the benefits of metabarcoding for expanding knowledge of aquatic biodiversity in the UK and elsewhere. Many of the ASVs associated with non-diatoms showed significant pressure responses; however, models that included non-diatoms had similar predictive strength to those based on diatoms alone. Whilst limitations of the primers for assessing non-diatoms may play a role in explaining these results, the diatoms provide a strong signal along the nutrient gradient and other algae, therefore, add little unique information. We recommend that future developments should use ASVs to calculate metrics, with links to reference databases made as a final step to generate lists of taxa to support interpretation. Any further exploration of the potential of non-diatoms would benefit from access to a well-curated reference database, similar to diat.barcode. Such a database does not yet exist, and we caution against the indiscriminate use of NCBI GenBank as a taxonomic resource as many rbcL sequences deposited have not been curated.

A taxonomy-free diatom eDNA-based technique for assessing lake trophic level using lake sediments

Anthropogenic eutrophication is one of the most pressing issues facing lakes globally. Our ability to manage lake eutrophication is hampered by the limited spatial and temporal extents of monitoring records, stemming from the time-consuming and expensive nature of physiochemical and biological monitoring. Diatom-based biomonitoring presents an alternative to traditional eutrophication monitoring, yet it is restricted by the high degree of taxonomic expertise required. Environmental DNA metabarcoding, while providing a promising substitute for diatom community enumeration, is plagued by inadequate taxonomic coverage of reference databases and methodological bias, limiting its use for biomonitoring. Here we show that taxonomy-free diatom-biomonitoring, in which environmental DNA metabarcoding data is utilised but not assigned to specific taxonomic classes, presents an accurate, fast, and relatively automated alternative to taxonomically assigned eutrophication biomonitoring. Our taxonomy-free index accounted for 85% of trophic level variability across 89 lakes and had the lowest average prediction error of the three approaches tested. By not relying on taxonomic identification or metabarcoding reference databases, taxonomy-free biomonitoring maintains diatom diversity that is lost in taxonomic assignment using molecular approaches. Furthermore, by utilising lake sediments, the approach outlined here presents a time-integrated estimation of lake trophic level and thus does not require time-consuming seasonal sampling. Taxonomy-free biomonitoring addresses the limitations of traditional physicochemical eutrophication monitoring and taxonomic biomonitoring alternatives and can be used to extend the spatial and temporal extents of eutrophication monitoring.

Paleo-diatom records reveal ecological change not detected using traditional measures of lake eutrophication

Lakes provide crucial ecosystem services and harbour unique and rich biodiversity, yet despite decades of research and management focus, cultural eutrophication remains a predominant threat to their health. Our ability to manage lake eutrophication is restricted by the lack of long-term monitoring records. To circumvent this, we developed a bio-indicator approach for inferring trophic level from lake diatom communities and applied this to sediment cores from two lakes experiencing eutrophication stress. Diatom indicators strongly predicted observed trophic levels, and when applied to sediment cores, diatom predicted trophic level reconstructions were consistent with monitoring data and land-use histories. However, there were significant recent shifts in diatom communities not captured by the diatom-based index or monitoring data, suggesting that conventional trophic level indices obscure important ecological change. New approaches, such as the one in this study, are critical to detect early changes in water quality and prevent the decline of lake ecosystems worldwide.